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May 25, 2026
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DTSC - 6410 Statistical Learning Models I (3)
A survey of statistical learning models for students with a background in statistics, for professional programs in which familiarity with supervised and unsupervised learning is needed. The topics include model selection for regression and classification, tree-based methods, dimension reduction, and clustering analysis. Provide students with the statistical learning model knowledge and the fundamental intuitions needed to use and develop effective machine learning/deep learning AI solutions for complex real-world problems. Instructional Method: LD Lecture-Discussion, HL Hybrid Lecture, OL Online Lecture Fall, Spring, Summer Admission to DTSC M.A. program
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